Semantic Search with S-BERT is all you need
Bloomberg - Semantic search is a data searching technique in a which a search query aims to not only find keywords, but to determine the intent and contextual meaning of the words a person is using for search.
Semantics refer to the philosophical study of meaning. It’s true that philosophy rarely rhymes with software engineering, but this concept does help us reach a definition. Indeed, Semantic Search is related to figuring out what your user means.
Semantic search seeks to improve search accuracy by understanding the content of the search query. In contrast to traditional search engines, that only finds documents based on lexical matches, semantic search can also find synonyms.
In fact, this type of search makes browsing more complete by understanding almost exactly what the user is trying to ask, instead of simply matching keywords to pages. The idea behind semantic search is to embed all entries in your corpus, which can be sentences, paragraphs, or documents, into a vector space.
At search time, the query is embedded into the same vector space and the closest embedding from your corpus are found. These entries should have a high semantic overlap with the query.
